在对工作流网模型的性质分析方面，提出了网系统的归约规则，将复杂的网系统归约化简后再进行分析。
As for the aspect of quality analysis for workflow net model, it proposes to simplify the complex net system by using some rules before the analysis.
详细论述了对基于有向有环图（DCG图）的工作流模型结构正确性进行验证的图归约法及其五种归约规则。
A graph reduction method with 5 rules for the structural correctness verification of DCG based workflow models is presented in this paper.
如果已经成功地归约了start规则(在这个例子中即file)，那么可以认为解析是成功的。
If the start rule (in this case, file) has successfully reduced, the parse is considered successful.
为了归约每个消息之后的规则，使用的是向左递归。
Left recursion is used so that the rule can be reduced after each message.
给出了数据约简方法，包括建立RS知识模型、RS决策逻辑表示、确定辨识矩阵、计算其核心、进行属性归约、规则形成等内容。
Information reduction method is given, in which includes RS knowledge modeling, RS decision logic expression, distinction matrix making, cores calculation, attributes reduction, rules generation, etc.
给出了数据约简方法，包括建立RS知识模型、RS决策逻辑表示、确定辨识矩阵、计算其核心、进行属性归约、规则形成等内容。
Information reduction method is given, in which includes RS knowledge modeling, RS decision logic expression, distinction matrix making, cores calculation, attributes reduction, rules generation, etc.
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